Type: Package
Title: Single-Cell Correlation Based Cell Type Annotation
Version: 0.1.1
Maintainer: Mohamed Soudy <Mohmedsoudy2009@gmail.com>
Description: Performing cell type annotation based on cell markers from a unified database. The approach utilizes correlation-based approach combined with association analysis using Fisher-exact and phyper statistical tests (Upton, Graham JG. (1992) <doi:10.2307/2982890>).
License: GPL (≥ 3)
Encoding: UTF-8
Imports: Seurat, dplyr, plyr, scales, HGNChelper, openxlsx
RoxygenNote: 7.3.0
NeedsCompilation: no
Packaged: 2024-03-13 10:48:54 UTC; mohamed.soudy
Author: Mohamed Soudy [aut, cre], Sophie LE BARS [aut], Enrico Glaab [aut]
Repository: CRAN
Date/Publication: 2024-03-13 11:40:02 UTC

Performs aggregation based on cell clusters and condition. Then, it calculates correlation matrix of genes

Description

This Function is used to perform cell aggregation by averaging the expression of scRNA-seq matrix and then perform correlation matrix

Usage

calculate_cor_mat(expression_mat, condition  = NULL, clusters, assay = "RNA")

Arguments

expression_mat

Seurat object that contains the expression matrix.

condition

column name of the condition in th meta data of the Seurat object.

clusters

column name of the cluster numbers in the meta data of the Seurat object.

assay

the assay to be used default is set to RNA

Value

correlation matrix of genes.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Calculate cell scores based on number of genes

Description

This Function is used to calculate cell scores based on number of genes

Usage

calculate_normalized_ratio(vec)

Arguments

vec

list of genes of cell types.

Value

vector of cell scores based on the number of overlapped genes with the input matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Process the cell markers names

Description

This Function is used to return the cell markers names processed for the sctype approach

Usage

correct_gene_symbols(markers)

Arguments

markers

list of unique cell markers.

Value

vector of genes names which overlap with the correlation matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Performs parallel function on two lists

Description

This Function is used to perform parallel function on two lists

Usage

enrich_genes(ref_list, overlap_list, func)

Arguments

ref_list

reference list.

overlap_list

overlap list.

func

function to be applied.

Value

list where each element is the result of applying the function 'func' to the corresponding elements of 'ref_list' and 'overlap_list'.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Filter the genes based on specific correlation threshold

Description

This Function is used to filter the gene correlation matrix based on user-defined threshold

Usage

filter_correlation(cor_mat, gene_list, threshold = 0.7)

Arguments

cor_mat

correlation matrix generated from calculate_cor_mat function.

gene_list

cell markers that passed threshold.

threshold

absolute correlation threshold.

Value

vector of gene names that pass user-defined correlation threshold.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Process the cell markers that overlap between the cell markers and scRNA matrix

Description

This Function is used to return the cell markers that overlap between the cell markers and scRNA matrix

Usage

filter_list(gene_list, passed_cells)

Arguments

gene_list

list of unique genes of cell types.

passed_cells

cells types that pass the specified threshold.

Value

list of cell types which genes are found in the input matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Performs fisher exact test to get the significant overlap between genes for cell type assignment

Description

This Function is used to perform fisher exact test to get cell types

Usage

fisher_test(ref, gene_overlap)

Arguments

ref

reference gene set.

gene_overlap

genes that pass the correlation threshold.

Value

vector of p-value and overlap.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Examples

fisher_test(c("PAX8","PAX6","TP53","AOC3","LIPF"), c("LIPF","PAX8","PAX6","TP53","TSHB","AOC3"))

Process the cell markers that pass specific threshold in the gene correlation matrix

Description

This Function is used to return the cell markers that pass specific threshold in the gene correlation matrix

Usage

match_characters(genes, gene_mat)

Arguments

genes

list of unique genes of cell types.

gene_mat

correlation matrix of genes.

Value

vector of genes names which overlap with the correlation matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Performs phyper test to get the significant overlap between genes for cell type assignment

Description

This Function is used to perform phyper test to get cell types

Usage

phyper_test(ref, overlap)

Arguments

ref

reference gene set.

overlap

genes that pass the correlation threshold.

Value

vector of p-value and overlap.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Examples

phyper_test(c("PAX8","PAX6","TP53","AOC3","LIPF"), c("LIPF","PAX8","PAX6","TP53","TSHB","AOC3"))

Gets the associated cell types using correlation-based approach

Description

This Function is used to get the associated cell clusters using correlation-based approach

Usage

process_clus(cluster,sobj,assay="RNA",clus,markers,cor_m,m_t=0.9,c_t=0.7,test="p")

Arguments

cluster

associated cluster name.

sobj

Seurat object.

assay

assay to be used default is set to RNA.

clus

cell clusters.

markers

cell markers database.

cor_m

gene correlation matrix.

m_t

overlap threshold between cell markers and expression matrix.

c_t

correlation threshold between genes.

test

statistical test that check if overlap is significant could be "p" for phyper or "f" for fisher.

Value

data frame of proposed cell types.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Process the database for the sctype approach

Description

This Function is used to process the database that will be used for sctype approach

Usage

process_database(database_name = "sctype", org = 'a', tissue, tissue_type = 'n')

Arguments

database_name

name of the database to be used that can be 'sctype' or 'UMD'.

org

name of organism to be used that can be 'h' for human, 'm' for mouse, and 'a' for all markers.

tissue

specified tissue from which the data comes.

tissue_type

tissue type whether 'a' for all types 'n' for normal tissues only or "c" for cancer tissues.

Value

vector of genes names which overlap with the correlation matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Process the cell markers database and return the processed list

Description

This Function is used to process the cell markers database and return the processed list

Usage

process_markers(markers_df)

Arguments

markers_df

data frame with markers named as gene_original and cell names as cell type.

Value

list of lists of the processed markers

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Run the pipeline for the cell type assignment

Description

This Function is used to run the main pipeline that does the cell type assignment

Usage

sccca(sobj,assay="RNA",cluster,marker,tissue,tt="a",cond,m_t=0.9,c_t=0.7,test="p",org="a")

Arguments

sobj

Seurat object.

assay

assay to be used default is set to RNA.

cluster

colname in the mata.data that have the cell cluster numbers.

marker

cell markers database path.

tissue

specified tissue from which the data comes.

tt

tissue type whether 'a' for all types 'n' for normal tissues only or "c" for cancer tissues.

cond

colname in the meta.data that have the condition names.

m_t

overlap threshold between cell markers and expression matrix.

c_t

correlation threshold between genes.

test

statistical test that check if overlap is significant could be "p" for phyper or "f" for fisher.

org

organism to be used that can be 'h' for human, 'm' for mouse, and 'a' for all markers.

Value

list of Seurat object that have the assigned clusters, and top 3 proposed cell types.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu

Run the sctype approach as it's implemented by Ianevski, A., Giri, A.K. and Aittokallio, T.

Description

This Function is used to run the sctype approach with faster implementation

Usage

sctype(sobj,assay="RNA",tissue,tt="a",clus,org="a",scaled=T,database="sctype")

Arguments

sobj

Seurat object.

assay

assay to be used default is set to RNA.

tissue

specified tissue from which the data comes.

tt

tissue type whether 'a' for all types 'n' for normal tissues only or "c" for cancer tissues.

clus

colname in the mata.data that have the cell cluster numbers.

org

organism to be used that can be 'h' for human, 'm' for mouse, and 'a' for all markers.

scaled

indicates whether the matrix is scaled (TRUE by default)

database

name of the database to be used that can be 'sctype' or 'UMD'

Value

vector of genes names which overlap with the correlation matrix.

Author(s)

Mohmed Soudy Mohamed.soudy@uni.lu and Sohpie LE BARS sophie.lebars@uni.lu and Enrico Glaab enrico.glaab@uni.lu